Consistency of Symptom Clusters in Advanced Cancer

Abstract

Background: The reproducibility of symptom clusters (SCs) in different populations would support the validity of the cluster concept. Ideal approaches to cluster identification are unknown. The presence of a sentinel (most prevalent) symptom may reduce the number of symptoms in a comprehensive symptom assessment tool. The primary purpose was to assess consistency of SCs between 2 independent data sets. A secondary aim was to evaluate whether use of a sentinel symptom might abbreviate assessment but retain acceptable accuracy. Methods: An agglomerative hierarchical cluster analysis in 922 patients with advanced cancer identified 7 SCs. We conducted the same analysis on an additional 181 cancer patients to assess cluster consistency. The most prevalent symptom within each cluster was defined as the ‘‘sentinel’’ symptom. Positive predictive value (PPV) and negative predictive value (NPV) were calculated to assess ability of the sentinel symptom to predict other symptoms in the cluster. Results: Similar clusters were identified in both data sets, which included nausea/vomiting, neuropsychologic, and aerodigestive clusters. When the sentinel symptom was present, >50% nonsentinel symptoms in a cluster were present; when absent, <50% nonsentinel symptoms were identified. However, the range for PPV and NPV of the sentinel symptom to identify other symptoms in the cluster was 19% to 72% and 41% to 95%, respectively. Conclusions: Consistent SCs were found in 2 separate data sets with the same assessment tool and statistical analysis. These findings support the statistical and clinical validity of the cluster concept through consistency between different populations. The nausea/vomiting, neuropsychologic, and aerodigestive clusters may be reliable for use in assessment. The presence or absence of a sentinel symptom in each cluster did not predict the presence or absence of other symptoms in the cluster. Sentinel symptoms are inadequate to assess symptom burden.